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long term choices
The usual school location choice models assign a usual school location for the primary mandatory activity of each child and university student in the synthetic population. The models are composed of a set of accessibility-based parameters (including one-way distance between home and primary destination and the tour mode choice logsum - the expected maximum utility in the mode choice model which is given by the logarithm of the sum of exponentials in the denominator of the logit formula) and size terms, which describe the quantity of grade-school or university opportunities in each possible destination.
The school location model is made up of four steps:
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sampling - selects a sample of alternative school locations for the next model step. This selects X locations from the full set of model zones using a simple utility.
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logsums - starts with the table created above and calculates and adds the mode choice logsum expression for each alternative school location.
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simulate - starts with the table created above and chooses a final school location, this time with the mode choice logsum included.
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shadow prices - compare modeled zonal destinations to target zonal size terms and calculate updated shadow prices.
These steps are repeated until shadow pricing convergence criteria are satisfied or a max number of iterations is reached.
The usual work location choice models assign a usual work location for the primary mandatory activity of each employed person in the synthetic population. The models are composed of a set of accessibility-based parameters (including one-way distance between home and primary destination and the tour mode choice logsum - the expected maximum utility in the mode choice model which is given by the logarithm of the sum of exponentials in the denominator of the logit formula) and size terms, which describe the quantity of work opportunities in each possible destination.
The work location model is made up of four steps:
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sample - selects a sample of alternative work locations for the next model step. This selects X locations from the full set of model zones using a simple utility.
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logsums - starts with the table created above and calculates and adds the mode choice logsum expression for each alternative work location.
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simulate - starts with the table created above and chooses a final work location, this time with the mode choice logsum included.
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shadow prices - compare modeled zonal destinations to target zonal size terms and calculate updated shadow prices.
These steps are repeated until shadow pricing convergence criteria are satisfied or a max number of iterations is reached.
Telecommuting is defined as workers who work from home instead of going to work. It only applies to workers with a regular workplace outside of home. The telecommute model consists of two submodels - this work from home model and a person Telecommute Frequency model. This model predicts for all workers whether they usually work from home.
The work from home model includes the ability to adjust a work from home alternative constant to attempt to realize a work from home percent for what-if type analysis. This iterative single process procedure takes as input a number of iterations, a filter on the choosers to use for the calculation, a target work from home percent, a tolerance percent for convergence, and the name of the coefficient to adjust. An example setup is provided and the coefficient adjustment at each iteration is: new_coefficient = log( target_percent / current_percent ) + current_coefficient.
The auto ownership model selects a number of autos for each household in the simulation. The primary model components are household demographics, zonal density, and accessibility.
The Free Parking Eligibility model predicts the availability of free parking at a person’s workplace. It is applied for people who work in zones that have parking charges, which are generally located in the Central Business Districts. The purpose of the model is to adequately reflect the cost of driving to work in subsequent models, particularly in mode choice.
Telecommuting is defined as workers who work from home instead of going to work. It only applies to workers with a regular workplace outside of home. The telecommute model consists of two submodels - a person Work From Home model and this person telecommute frequency model.
For all workers that work out of the home, the telecommute models predicts the level of telecommuting. The model alternatives are the frequency of telecommuting in days per week (0 days, 1 day, 2 to 3 days, 4+ days).
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